{
  "annotation_id": "82469bef-48a8-4fa2-93b8-536572bb6bfe",
  "date_created": "2026-03-02T18:01:52.864000Z",
  "date_modified": "2026-03-02T18:01:52.864000Z",
  "file_hash": "5394772e6a027c58c534572c05316f5fef22ae65f6958045b42ba34f7ee99fcc",
  "private": false,
  "record": {
    "abstract": "By means of a simple example it is demonstrated that the task of finding and\nidentifying certain patterns in an otherwise (macroscopically) unstructured\npicture (data set) can be accomplished efficiently by a quantum computer.\nEmploying the powerful tool of the quantum Fourier transform the proposed\nquantum algorithm exhibits an exponential speed-up in comparison with its\nclassical counterpart. The digital representation also results in a\nsignificantly higher accuracy than the method of optical filtering. PACS:\n03.67.Lx, 03.67.-a, 42.30.Sy, 89.70.+c.",
    "arxiv_id": "quant-ph/0208063",
    "authors": [
      "Ralf Sch\u00fctzhold"
    ],
    "categories": [
      "quant-ph"
    ],
    "doi": "10.1103/PhysRevA.67.062311",
    "title": "Pattern recognition on a quantum computer",
    "url": "https://arxiv.org/abs/quant-ph/0208063"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "846d3cdc-02a9-4faa-bd5e-fd61a2a36567",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}